@article{HaubeltNeubauerSchaubetal.2018,
  author    = {Haubelt, Christian and Neubauer, Kai and Schaub, Torsten H. and Wanko, Philipp},
  title     = {Design space exploration with answer set programming},
  series = {K{\"u}nstliche Intelligenz},
  volume    = {32},
  journal   = {K{\"u}nstliche Intelligenz},
  number    = {2-3},
  publisher = {Springer},
  address   = {Heidelberg},
  issn      = {0933-1875},
  doi       = {10.1007/s13218-018-0530-3},
  pages     = {205 -- 206},
  year      = {2018},
  abstract  = {The aim of our project design space exploration with answer set programming is to develop a general framework based on Answer Set Programming (ASP) that finds valid solutions to the system design problem and simultaneously performs Design Space Exploration (DSE) to find the most favorable alternatives. We leverage recent developments in ASP solving that allow for tight integration of background theories to create a holistic framework for effective DSE.},
  language  = {en}
}
@misc{NeubauerHaubeltWankoetal.2018,
  author    = {Neubauer, Kai and Haubelt, Christian and Wanko, Philipp and Schaub, Torsten H.},
  title     = {Utilizing quad-trees for efficient design space exploration with partial assignment evaluation},
  series = {2018 23rd Asia and South Pacific Design Automation Conference (ASP-DAC)},
  journal   = {2018 23rd Asia and South Pacific Design Automation Conference (ASP-DAC)},
  publisher = {IEEE},
  address   = {New York},
  isbn      = {978-1-5090-0602-1},
  issn      = {2153-6961},
  doi       = {10.1109/ASPDAC.2018.8297362},
  pages     = {434 -- 439},
  year      = {2018},
  abstract  = {Recently, it has been shown that constraint-based symbolic solving techniques offer an efficient way for deciding binding and routing options in order to obtain a feasible system level implementation. In combination with various background theories, a feasibility analysis of the resulting system may already be performed on partial solutions. That is, infeasible subsets of mapping and routing options can be pruned early in the decision process, which fastens the solving accordingly. However, allowing a proper design space exploration including multi-objective optimization also requires an efficient structure for storing and managing non-dominated solutions. In this work, we propose and study the usage of the Quad-Tree data structure in the context of partial assignment evaluation during system synthesis. Out experiments show that unnecessary dominance checks can be avoided, which indicates a preference of Quad-Trees over a commonly used list-based implementation for large combinatorial optimization problems.},
  language  = {en}
}
@misc{NeubauerWankoSchaubetal.2017,
  author    = {Neubauer, Kai and Wanko, Philipp and Schaub, Torsten H. and Haubelt, Christian},
  title     = {Enhancing symbolic system synthesis through ASPmT with partial assignment evaluation},
  series = {Proceedings of the Design, Automation \& Test in Europe Conference \& Exhibition (DATE), 2017},
  journal   = {Proceedings of the Design, Automation \& Test in Europe Conference \& Exhibition (DATE), 2017},
  publisher = {IEEE},
  address   = {New York},
  isbn      = {978-3-9815370-9-3},
  issn      = {1530-1591},
  doi       = {10.23919/DATE.2017.7927005},
  pages     = {306 -- 309},
  year      = {2017},
  abstract  = {The design of embedded systems is becoming continuously more complex such that efficient system-level design methods are becoming crucial. Recently, combined Answer Set Programming (ASP) and Quantifier Free Integer Difference Logic (QF-IDL) solving has been shown to be a promising approach in system synthesis. However, this approach still has several restrictions limiting its applicability. In the paper at hand, we propose a novel ASP modulo Theories (ASPmT) system synthesis approach, which (i) supports more sophisticated system models, (ii) tightly integrates the QF-IDL solving into the ASP solving, and (iii) makes use of partial assignment checking. As a result, more realistic systems are considered and an early exclusion of infeasible solutions improves the entire system synthesis.},
  language  = {en}
}
@misc{NeubauerWankoSchaubetal.2018,
  author    = {Neubauer, Kai and Wanko, Philipp and Schaub, Torsten H. and Haubelt, Christian},
  title     = {Exact multi-objective design space exploration using ASPmT},
  series = {Proceedings of the 2018 Design, Automation \& Test in Europe Conference \& Exhibition (DATE)},
  journal   = {Proceedings of the 2018 Design, Automation \& Test in Europe Conference \& Exhibition (DATE)},
  publisher = {IEEE},
  address   = {New York},
  isbn      = {978-3-9819-2630-9},
  issn      = {1530-1591},
  doi       = {10.23919/DATE.2018.8342014},
  pages     = {257 -- 260},
  year      = {2018},
  abstract  = {An efficient Design Space Exploration (DSE) is imperative for the design of modern, highly complex embedded systems in order to steer the development towards optimal design points. The early evaluation of design decisions at system-level abstraction layer helps to find promising regions for subsequent development steps in lower abstraction levels by diminishing the complexity of the search problem. In recent works, symbolic techniques, especially Answer Set Programming (ASP) modulo Theories (ASPmT), have been shown to find feasible solutions of highly complex system-level synthesis problems with non-linear constraints very efficiently. In this paper, we present a novel approach to a holistic system-level DSE based on ASPmT. To this end, we include additional background theories that concurrently guarantee compliance with hard constraints and perform the simultaneous optimization of several design objectives. We implement and compare our approach with a state-of-the-art preference handling framework for ASP. Experimental results indicate that our proposed method produces better solutions with respect to both diversity and convergence to the true Pareto front.},
  language  = {en}
}